ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

Jinming Zhang

doi:10.1002/j.2333-8504.2005.tb01981.x

ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE

Research output: Contribution to journal › Article

Abstract

This study derived an expectation‐maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM‐GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM‐GA algorithm. The simulation results demonstrate that the EM‐GA algorithm is a very promising approach in estimating multidimensional item response model parameters.

Original language	English (US)
Pages (from-to)	i-38
Journal	ETS Research Report Series
Volume	2005
Issue number	1
DOIs	https://doi.org/10.1002/j.2333-8504.2005.tb01981.x
State	Published - Jun 1 2005
Externally published	Yes

Keywords

genetic algorithm
GA
EM-GA algorithm
ASSEST
estimation
multidimensional item response theory
MIRT
mixed structure
approximate simple structure

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Zhang, J. (2005). ESTIMATING MULTIDIMENSIONAL ITEM RESPONSE MODELS WITH MIXED STRUCTURE. ETS Research Report Series, 2005(1), i-38. https://doi.org/10.1002/j.2333-8504.2005.tb01981.x

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